The Air and Sound Pollution Monitoring System using Internet of Things and Cloud Based Data Analysis - Deshinta, Arrova Dewi; Lai, Edward Poh Yen; Ponkoodalingan, Kannan (INTI International University, 2018)
The Air and Sound Pollution Monitoring System (ASPMS) is a new concept that can be used in many sectors like industry, home living, road and transportation, environmental surroundings, etc. Currently, the ASPMS has been developed as separate entity whereby the users need to activate two systems in order to use them. With Internet of Things (IoT) technology, both entities are combined to promote user friendliness. In this paper, not only both entities are combined, the proposed ASPMS is linked to cloud based service that enable users to see the graphical view of the sensor readings. The overall system receives data from relevant sensors and administered by a portable processor Raspberry Pi. In this study, the important sensors are employed, like MQ135 that is used as gas sensor, MQ7 for measuring the CO2 level, and DHT11 for measuring temperature and humidity. Altogether, the values are analysed to define the pollution level. The connection is established using MQTT broker (Message Queuing Telemetry Transport). This design ensures a real-time monitoring system upon the quality of air and sound levels. A dedicated website is developed to contain variety of data which can be used for important action and precaution of a sudden pollution, for example, wearing masks or automatically switch-on a connected purifier device to protect the air quality in a building. The ASPMS is implemented using Java language, connected with Thingspeak, and openHab for system integration. The result shows a real-time pollution data are able to captured, monitored and analyzed accurately as per requirement.